Decoding the role of oxidative stress resistance and alternative carbon substrate assimilation in the mature biofilm growth mode of Candida glabrata

Background Biofilm formation is viewed as a vital mechanism in C. glabrata pathogenesis. Although, it plays a significant role in virulence but transcriptomic architecture and metabolic pathways governing the biofilm growth mode of C. glabrata remain elusive. The present study intended to investigate the genes implicated in biofilm growth phase of C. glabrata through global transcriptomic approach. Results Functional analysis of Differentially expressed genes (DEGs) using gene ontology and pathways analysis revealed that upregulated genes are involved in the glyoxylate cycle, carbon-carbon lyase activity, pre-autophagosomal structure membrane and vacuolar parts whereas, down- regulated genes appear to be associated with glycolysis, ribonucleoside biosynthetic process, ribosomal and translation process in the biofilm growth condition. The RNA-Seq expression of eight selected DEGs (CgICL1, CgMLS1, CgPEP1, and CgNTH1, CgERG9, CgERG11, CgTEF3, and CgCOF1) was performed with quantitative real-time PCR (RT-qPCR). The gene expression profile of selected DEGs with RT-qPCR displayed a similar pattern of expression as observed in RNA-Seq. Phenotype screening of mutant strains generated for genes CgPCK1 and CgPEP1, showed that Cgpck1∆ failed to grow on alternative carbon substrate (Glycerol, Ethanol, Oleic acid) and similarly, Cgpep1∆ unable to grow on YPD medium supplemented with hydrogen peroxide. Our results suggest that in the absence of glucose, C. glabrata assimilate glycerol, oleic acid and generate acetyl coenzyme-A (acetyl-CoA) which is a central and connecting metabolite between catabolic and anabolic pathways (glyoxylate and gluconeogenesis) to produce glucose and fulfil energy requirements. Conclusions The study was executed using various approaches (transcriptomics, functional genomics and gene deletion) and it revealed that metabolic plasticity of C. glabrata (NCCPF-100,037) in biofilm stage modulates its virulence and survival ability to counter the stress and may promote its transition from commensal to opportunistic pathogen. The observations deduced from the present study along with future work on characterization of the proteins involved in this intricate process may prove to be beneficial for designing novel antifungal strategies. Supplementary Information The online version contains supplementary material available at 10.1186/s12866-024-03274-9.


Introduction
Candidemia, and other forms of invasive candidiasis (IC) caused by different Candida species are unquestionably the most prevalent form of invasive mycoses worldwide, especially in paediatric wards and intensive care units (ICUs) [1][2][3].Individuals suffering with diabetes, immune deficiencies, hematologic malignancies as well those using indwelling medical devices, receiving parenteral nutrition or undergoing prior surgeries due to other morbidities are most susceptible to candidemia and IC [4][5][6].A global antifungal surveillance program, reported that patients suffering from candidemia and IC had a remarkable shift in the prevalence of Candida species towards non-albicans Candida (NAC) species [3].Amongst NAC species, Candida glabrata has been reported to be the leading pathogen accounting for 10-35% of total bloodstream infections that alone causes 30-90% mortality [3,7,8].Moreover, the elevated emerging incidence of C. glabrata infections have raised serious health concerns in the recent past due to its inherent drug resistance towards azole-based antifungal drugs, co-resistance to the amphotericin-B and echinocandins (the latest antifungal agent) as well as stealth immune evasion strategy, making it difficult to manage and treat in ICU settings [2,3,9].C. glabrata, a haploid yeast, is mainly found as a commensal in the oral cavity, gut, and vaginal tract of humans but in immunocompromised individuals it may cause candidemia and candidiasis due to its virulence attributes such as phospholipases, lipases, haemolysins, GPI-linked aspartyl proteases and having intracellular replicative capacity within host macrophages [10,11].More specifically, C. glabrata has a strong biofilm formation potential making it more resistant to various interventions [9,12,13].Biofilm formation is a potent virulence factor for the pathogenesis of C. glabrata as it forms protective sheath that imparts antifungal drug resistance by mainly inhibiting the penetrating ability of antifungal drugs vis-a-vis eradication of biofilm leading to persistence and dissemination of infection in host and helps in immune evasion of the host to provide an impeccable strategy in clinical infection [14,15].Biofilm resistance in Candida species has been reported because of overexpression of efflux pumps, composition cell wall, increased cell density and presence of thick extracellular matrix [16][17][18].The environmental stress conditions, nutritional access, and availability of oxygen determine the biological activities of cells in biofilm growth mode [19].In this context, a few key questions need be addressed to understand the pathogenomics of biofilm of the C. glabrata such as (i) What are the systemic level alterations occurring in the mature biofilm cells of C. glabrata and (ii) How differential expression of gene regulate the cellular and molecular functions that contribute to the stress resistance in the biofilm.Thus, it is pertinent to identify the genes and gene sets involved in the biological pathways and understand how they maintain the integrity of mature biofilm and disseminate C. glabrata infection in the host.Moreover, various alterations occur in the biofilm cells at genomics, transcriptomics and proteomics level.Although, few candidate genes have been observed to be associated with biofilm formation in C. glabrata [12,20,21], but detailed investigations of how large gene sets and their regulatory networks shape this intricate process has not been deciphered yet.Transcriptomic studies have well documented the profiling of differential expression of genes (DEGs) in varied environmental and stress conditions such as pH, nitrosative, and antifungal stress encountered by C. glabrata [22][23][24].However, the differential expression of genes and how their functional attributes regulate the metabolic pathways and biological processes to withstand the varied stresses (environmental stress, antifungal stress and host immune response) prevailing in the mature biofilm of C. glabrata still needed to be elucidated.Therefore, comparative transcriptome profiling between planktonic and biofilm conditions in C. glabrata (NCPPF-100,037) along with the functional characterisation of the significantly upregulated gene, may provide useful information about the regulatory network of genes and its pathotranscriptomics. Gene set enrichment analysis, metabolic pathways, and functional analysis of DEGs associated with the biofilm growth phase of C. glabrata, facilitate the identification and functional visualization of the genes implicated in metabolic network re-wiring in response to the stress conditions prevailing in this phase and augmented its virulence fitness attributes.Thus, for a better understanding of pathobiology in C. glabrata at the transcriptomic and molecular level, the present study was designed with an aim to decipher differentially expressed genes (DEGs), vis-a-vis functional characterization of selected genes involved in the biofilm formation of C. glabrata (NCCPF-100,037).

Quantification of biofilm forming potential
i. Crystal violet assay: 100 µL of log phase culture (10 6  CFU/mL) of all C. glabrata strains were added to polystyrene 96-well microtiter plate in SDB medium and medium without any cells served as a control.The plates were incubated for 24 h at 37 °C and thereafter, medium was carefully aspirated without disrupting the biofilm formed, washed with sterile PBS followed by addition of 0.2% crystal violet and incubated at 37 °C for 10-15 min.Plates were washed with PBS, dried, 100 µL of 30% acetic acid was added to each well to solubilize the stain and again incubated at 37 °C for 10-15 min.Solubilized crystal violet (100 µL) was transferred to a fresh microtiter plate and optical density (O.D) was measured at 550 nm using a microtiter plate reader (Biotek Microplate reader, USA) with 30% acetic acid as a blank [25,26].ii.XTT assay (2,3-Bis-(2-Methoxy-4-Nitro-5-Sulfophenyl)-2 H-Tetrazolium-5-Carboxanilide) :100 µL of XTT/menadione solution was added to each well containing a pre-washed biofilm as well as to the negative controls.The plates were incubated in the dark for 2 h at 37 °C.The supernatant (80 µL) from each well was transferred to a new microtiter plate and the absorbance was measured at 490 nm using a microtiter plate reader (Biotek Microplate reader, USA) [25].iii.

Confocal laser scanning microscopy (CLSM)
:Biofilm was prepared over coverslip in a 6-well tissue culture plate.The conditions for biofilm formation were the same as described in Sect.2(i).
Once the biofilm is formed over the coverslips, 2 mL of dye mix was added containing FUN-1[2 chloro 4(2,3 dihydro-3-methyl (benzo-1,3-thiazol 2-yl)-methylidene) 1 phenyl quinolinium iodide] in PBS and incubated for 30-35 min at 37 °C.The coverslip was then gently removed from the dye mix and placed on a 35 mm glass bottom petri dish.Biofilm was examined under confocal scanning laser microscope at 63.3X (Leica SP5 II system, Leica Microsystems, India) [27].Z-stack images were also captured at the same magnification for 3-D image reconstruction.

RNA sequencing
Clinical isolate C. glabrata (NCCPF-100,037), showing the best biofilm forming ability was selected for RNA isolation and sequencing.Briefly, 100 µL of log phase culture (10 6 CFU/mL) was added in each well of the 6-well tissue culture plate and incubated at 37 °C for 24 h under static conditions.The biofilm cells from were scrapped off with a scrapper.Cells from biofilm and planktonic growth phases were subjected to enzymatic treatment with lyticase at 37 °C for 1 h.RNA was extracted using Hi-PurA yeast RNA purification kit (Hi-Media, Laboratories Pvt. Ltd.India) as per manufacturer's instructions [28].The concentration, purity and quality of isolated RNA was assessed using Nanodrop1000 spectrophotometer (Thermo Scientific, USA).Briefly, 1 µL of extracted RNA was used in the apparatus and RNA absorbance ratio was observed at 260 nm and 280 nm.Furthermore, gene IDs were assigned to each network using the Cluepedia application [33][34][35].

Verification of DEGs with RT-qPCR
RNA-Seq expression of selected DEGs was verified with real-time quantitative PCR (RT-qPCR).RT-qPCR was performed with RNA isolated from mature biofilm (test) and planktonic cells (control) of C. glabrata.The cDNA was synthesized from RNA with a reverse transcription verso kit (Thermo Fisher Scientific, USA).RT-qPCR was performed with StepOnePlus real-time machine (Applied Biosystem, USA) using SYBER green PCR master mix (Applied Biosystem, USA) according to the manufacturer's instructions.Each reaction mixture was set up in triplicate of 20 µL volume with 20 ng of cDNA and run for 40 cycles (Thermo-cycler conditions, initial holding step at 95 °C for 10 min, followed by 40 cycles at 95 °C each for 15 s and 60 °C for 1 min annealing/extension).The gene expression was determined using C T method and normalized with housekeeping gene CgRDN18-1(18 S-rDNA) [36].A list of primers used to amplify the target genes is given in (Supplementary Table S1).The following equation was used to calculate the fold change of gene expression between biofilm and planktonic growth phase.

Functional validation of selected genes
i. Yeast colony PCR :Zymolyase (MP Biomedicals) treatment was performed to digest the cell wall and obtain spheroplasts.For this, a zymolyase cocktail or digestion cocktail [zymolyase (2 mg/mL) and sorbitol (1.2 M)] was prepared in PBS and 10 µL aliquots were dispensed into 0.2 mL PCR tubes.A tip-full of yeast cells from a single colony or purified yeast transformant were added to the tubes and incubated at 37 °C for 3-4 h.The PCR mix was made with the appropriate primer set and 1 µL of the zymolyasedigested cell suspension was added as a template to perform PCR.Gel extraction for the amplified PCR product was performed using QIAgen kits (QIAgen Pvt Ltd, Germany) and protocols were followed, according to the manufacturer's instructions.ii.Cassettes construction :Open reading frames (ORFs) of CgPCK1 andCgPEP1 of C. glabrata were deleted by homologous recombination with Nat1 gene deletion cassette [37].A cassette containing the Nat1 gene was used, which encodes nourseothricin acetyltransferase (NAT) and imparts resistance to nourseothricin and replaces the gene of interest with the Nat1, the sequence of pRK625 plasmid is presented in appendix-A.The Nat1 gene was amplified using PCR from the pRK625 plasmid in two halves carrying a common 310 bp overlapping region between them.Subsequently, the 5' and 3' untranslated regions (UTR) of the target gene from genomic DNA from the wild-type clinical isolate of C. glabrata were amplified using respective primers with amplified PCR products of approximately 500-550 bp size.The Nat1 deletion cassette was synthesized by fusion PCR from both 5'-and 3'-UTR region of a target gene (CgPCK1 and CgPEP1) and each half of the Nat1 gene derived from amplification of pRK625 plasmid using overhang primers (fusion product 1 (FP1) = 5' nat1 + 5'UTR region of a target gene, fusion product 2 (FP2) = 3'

Statistical analysis
The GraphPad Prism software was used to plot data and graphical analysis.The two-tailed student's t-test was used for comparative intergroup analysis and spearman's correlation regression analysis was used for scatter plot of gene expression.A p-value of < 0.05 and with 5% FDR was considered significant.

Quantification of biofilm-forming capacity
The biofilm forming capacity of all the tested strains of C. glabrata (clinical iso-lates NCCPF-100,029, NCCPF-100,033, NCCPF-100,037, standard strains ATCC-2001 & MTCC-3019) revealed that C. glabrata (ATCC-2001) has the maximum biofilm formation potential, followed by the clinical isolate NCCPF-100,037, in terms of biomass and metabolic activity (Fig. 1).The total biomass of all strains, measured with crystal violet (CV), showed an increasing trend up to 120 h (Fig. 1a) with C. glabrata (ATCC-2001) strains producing the highest biomass in the biofilm growth phase.The evaluated metabolic activity with 2,3-Bis-(2-Methoxy-4-Nitro-5-Sulfophenyl)-2 H-Tetrazolium-5-Carboxanilide) (XTT) was observed maximum at 24 h for all the tested strains and then gradually decreased up to 120 h.Among all, C. glabrata (ATCC-2001) and C. glabrata (NCCPF − 100,037) displayed maximum and almost comparable metabolic activity up to 120 h (Fig. 1b).CLSM biofilm images at different contrasts and angles for all strains showed that they also possess similar red fluorescence filaments (Fig. 2 II, a-e).Furthermore, the vertical (x, z) section or side views of the reconstructed 3-D image revealed that all strains exhibited almost same thickness and architecture of biofilm and 3-D projection images with z stacks also showed that they have a biofilm thickness of around 250 µM (Fig. 2 III, a-e). in terms of the RNA integrity number (RIN) of all biological replicates of both growth conditions (planktonic and biofilm) was found to be 9.8, 9.9 7.7, 9.6, 9.5 & 9.8 in planktonic-I, II, III, biofilm-I, II & III, respectively, (Supplementary Figs.S1, S2).The average GC content of all the sequenced samples was found to be 44.98% and alignment percentage of clean read generated from biofilm-I, biofilm-II, biofilm-III, planktonic-I, planktonic-II, and planktonic-III using TopHat-2 over reference genome of C. glabrata was observed 76.S4), respectively.The raw read files of RNA-Seq and the expression matrix features of the study were submitted to the National Centre for Biotechnology Institute Gene Expression Omnibus database (NCBI-GEO) with project ID: PRJNA640406.Expression analysis obtained a significant 959 (almost 18%) DEGs out of total 5294 genes from C. glabrata genome.The whole transcriptomic data employing after the cut-off value of +/-1.5 to the log2FC (+ 1.5 for up-regulated & -1.5 for down-regulated) with adjusted p-value or (FDR) of < 0.05 resulted into a 363 (6.85%) up-regulated and 596 (11.26%) down-regulated genes respectively under mature biofilm growth phase.

Visualization of the RNA-Seq data
Gene expression measured in terms of FPKM values (normalized gene expression ) in both conditions (planktonic vs. biofilm) of C. glabrata plotted with a scatter plot revealed that there is a large and significant variation of gene expression under mature biofilm growth phase compared to planktonic condition (Supplementary Fig. S3).The variation in a global transcriptomic landscape under mature biofilm growth phase of C. glabrata was depicted in graphical visualization with volcano plots (Fig. 3 & Supplementary Fig. S4).DEGs calculated in terms of log2 fold change (log 2 FC) FPKM values between two distinct growth conditions (biofilm and planktonic) were plotted against the p-value (-log10 p-value).The red and green dots of the volcano plot represent the most significant up-regulated genes and down-regulated genes with high log 2 FC of FPKM values along with their statistical significance (very low p-value).This suggests, that genes such as CAGL0H010076g, CAGL0M07920g play playing a potential role in the biofilm lifestyle of C. glabrata.The list of top significant DEGs with log 2 FC (1.5 for up-regulated & -1.5 for down-regulated) and normalized z − scores of both growth conditions were visualized using heatmap (Fig. 4).The log 2 FC values under the two conditions (biofilm and planktonic phase) were presented in hierarchical clusters along with their adjusted p-values (FDR).Columns of the heatmap grid representing the growth condition (biofilm and planktonic) and rows represent the differentially expressed genes, whereas the color intensity of the rows displays the expression level across the two conditions (planktonic and biofilm).Gene IDs along with their characterized or putative protein encoded by the respective genes are also shown on the right side of the heat map, and the left side shows the coexpression level dendrogram of the genes.

Gene set enrichment and pathways analysis of DEGs
RNA-Seq data was subjected to elucidate functional enrichment analysis of significantly DEGs, based on their gene ontology and pathways involved in the mature biofilm growth phase of C. glabrata (NCCPF-100,037).The most significant list of up-regulated and down-regulated genes were processed separately with ClueGO for analysis of the gene ontology (GO) /Kyoto Encyclopedia of Genes and Genomes (KEGG).The functional annotation enrichment analysis revealed that enriched up-regulated genes are involved in the cellular carbohydrate metabolism, depicted in green color nodes with a molecular function such as glyoxylate and dicarboxylate metabolism, carbon-carbon lyase activity, monocarboxylate, tricarboxylate, citrate metabolism, precursor metabolite generation and energy generation in biofilm cells (Fig. 5).Genes in red color nodes are involved in the cellular catabolic processes of a cell that are responsible for the regulation of autophagy, autophagy, pre-autophagosomal structure, pre-autophagosomal structure membrane, vacuole and vacuolar part.Similarly, orange color nodes depict the genes involved in mitochondrial inner membranes and organelle envelope, whereas pink color nodes demonstrate the fatty acid and lipid metabolic process of peroxisomes.The percentage of genes associated with their biological terms were represented graphically (Supplementary Fig. S5).The names of C. glabrata genes associated with biofilm formation are shown in red on the network pathways and the size of the nodes on the network pathways corresponds to the statistical significance of biological terms.

Functional characterization of
The fusion PCR of these products one by one with amplified Nat1 gene generated FP1 and FP2 of size 1377 bp (lane-1) and 1490 bp (lane-2) observed on agarose gel (1.5%) (Supplementary Fig. S7b).ii.Verification of genes (CgPCK1and CgPEP1) disruption inC.glabrata(NCCPF-100,037): PCR amplified product with internal primers for target gene CgPCK1 demonstrated the absence of this gene in genomic DNA isolated from the transformant mutant strains C. glabrata (NCCPF-100,037 or Cgpck1∆).There was no amplification observed (of CgPCK1 gene) in lanes 5-13, and lane-1 represent the marker of 100 bp (Supplementary Fig. S8).Whereas, PCR product of size 334 bp were amplified with internal primer from genomic DNA of wild type C. glabrata (NCCPF-100,037) strain in lanes 2&4.Further, PCR amplification of full Nat1 cassette from genomic DNA of C. glabrata (NCCPF-100,037) mutant (transformants) strain confirmed its insertion in place of target knockedout CgPCK1 gene.PCR amplification with expected product size of full Nat1 cassette (547 bp) was observed in the lanes (2, 4, 6, 8, 9, 10 and 11) from genomic DNA of C. glabrata (NCCPF-100,037) mutant strains (transformants), conversely there was no amplification observed in no template control (NTC) (lane-12) and wild-type genomic DNA template (lane-13) (Supplementary Fig. S8).This is verified that the cassette has been inserted exactly in the place of target gene and resulted in a knock-out strain of C. glabrata (NCCPF-100,037) for Cgpck1∆ strain.There was no amplification observed from the genomic DNA of wild type C. glabrata (NCCPF-100,037) in lane-13, lane-1 show the molecular marker M of size 100 bp (b) The lane-2, shows the PCR amplified product of a size 302 bp using internal primer for gene CgPEP1 with genomic DNA from wild type C. glabrata (NCCPF-100,037) and taken as a positive control.Lanes 4-17 showed no PCR amplification using internal primer for gene CgPEP1 with genomic DNA isolated from the Cgpep1∆ mutant (transformants), conversely lane-3 showed PCR amplified product of a size 302 bp with Cgpep1∆ mutant DNA.Similarly, PCR with internal primers for target gene CgPEP1 from the genomic DNA isolated from the transformant mutant strains C. glabrata (NCCPF-100,037 or Cgpck1∆ showed no amplification in lanes 4-17 (Supplementary Fig. S9a).Whereas, genomic DNA from wild type strains of C. glabrata (NCCPF-100,037) showed the amplification of PCR band of size 302 bp with internal primer for CgPEP1 gene (Supplementary Fig. S9b).Additionally, genomic DNA from mutant strains (transformant) of C. glabrata (NCCPF-100,037) showed amplification of full Nat1 cassette in lanes 2-11 (Supplementary Fig. 9b).whereas,DNA from wild of the same strain displayed absence of any PCR band in lane 13 confirms the knocking-out of CgPEP1(Supplementary Fig. S9).iii.Phenotype screening of knockout strains: The knocking out of genes was followed by the functional validation of CgPCK1 and CgPEP1 in response to the nutritional limitations and stresses.Growth phenotype of C. glabrata strains lacking CgPCK1 and CgPEP1 genes was observed on alternative carbon sources such as glycerol, ethanol and linoleic acid).Growth and viability of mutants strains were also checked in the presence of antifungal agent (fluconazole), oxidative stress inducers (menadione, H 2 O 2 ) and in metal ion stress (MnCl 2 ) conditions.Analysis of growth phenotype screening revealed that Cgpck1∆ mutant failed to grow on yeast nutrients broth (YNB) plates supplemented with alternative carbon sources such as glycerol, ethanol and linoleic acid.Furthermore, its growth and viability remained unaltered in the media in presence of fluconazole, metal stress inducer (MnCl 2 ) and oxidative stressors such as menadione and hydrogen peroxide H 2 O 2 (Fig. 7).This suggested that Cgpck1∆ mutant unable to utilize the carbon substrates other than glucose such as glycerol, ethanol and linoleic acid.On the other hand, Cgpck1∆ mutant could withstand the fluconazole, metal stress and oxidative stressors.Furthermore, Cgpep1∆ showed growth on alternative carbon substrates (glycerol, ethanol and linoleic acid), fluconazole and stress inducers such as menadione and (MnCl 2 ) but it failed to grow in presence of H 2 O 2 (Fig. 8).This indicates that CgPEP1 is associated with oxidative stress in the clinical isolate C. glabrata (NCCPF-100,037).

Discussion
Metabolic plasticity prevailing in biofilm growth phase of C. glabrata needs to be unraveled in order to understand its pathobiology and designing novel antifungal regimen to tackle infections caused by this pathogen.
The observations of biofilm forming assays (qualitative, quantitative) and microscopic analysis (morphology and architecture) of biofilm cells indicated that among all the three clinical strains of C. glabrata (NCPPF-100,037, NCPPF-100,033, NCPPF-100,029), C. glabrata (NCCPF-100,037) is a strong biofilm former and its biofilm capacity is almost similar to that of the standard strain of C. glabrata CBS-138 (ATCC-2001), which has been previously reported as a potent biofilm former [20,40].Therefore, the present study was designed to identify genes involved in sustaining mature biofilm growth phase of C. glabrata-NCCPF-100,037 isolated from a patient with blood-stream infection (BSI)/candidemia and happens to be more virulent after overcoming the host immune defence mechanisms during the host-pathogen interaction, (ii) Standard laboratory strains might have lost the important genes responsible for biofilm formation while repeated culturing in the laboratory [41][42][43].Furthermore, a recent study reported significant differences in the surface hydrophobicity, oxidative stress induction and susceptibility to azole based antifungal drug, between clinical isolates and standard strains of C. glabrata [44].This prompted us to use clinical strains of C. glabrata for transcriptomics investigation.The RNA-Seq based transcriptomics approach has been pivotal in cataloguing the landscape of gene structure, profiling transcriptome expression and functional genome characterization under varied conditions of the pathogen [45,46].Here, we attempted to demonstrate how differential expression of genes remodel the cells to counter the nutrient and oxidative stress in biofilm growth conditions in C. glabrata.In the present study, most of the significant DEGs obtained are uncharacterized and their functions are not verified to date, comprising 72.51% (694) of the total observed DEGs (959).A possible reason for this could be that only 530 (10%) of the total 5271 ORFs of C. glabrata have been confirmed and characterized so far, whereas C. albicans has 3598 (29%) out of 12,405 ORFs which is nearly three times the former [47,48].This suggests that genomics and transcriptomics of C. glabrata are understudied and more research into genome annotation and characterization of this opportunistic pathogen is required.The extensive data visualization plots identified and screened significant DEGs out of a large data set that may be involved in the biofilm growth modes [32,49].
The observations of functional annotation, gene ontology, and pathways analysis pointed out that significant upregulated DEGs are involved in carboxylic acid catabolism, carboxylic acid transport, glyoxylate cycle, monocarboxylic acid catabolism, oxidoreductase activity, propionate catabolic process, and 2-methyl citrate cycle.These observations are in accordance with previous reports where transcriptomics and proteomics findings of C. glabrata have suggested that upregulated genes are involved in alternative carbon substrate utilization of stress related proteins and down-regulation of glycolytic pathways under biofilm growth conditions [50][51][52].These results indicate that C. glabrata experiences various stress conditions and nutritional shortages throughout the mature growth phase.Therefore, expression of stress resistance genes are elevated and those involved in glycolytic pathways are downregulated to save the energy supply.In contrast, transcriptomics and functional gene analysis of high biofilm former C. albicans reported the upregulated pathways are associated with amino acid (including arginine, aspartate, glutamate and proline), fatty acid and pyruvic acid metabolism [53][54][55].More specifically, verification of the differentially expressed genes and functional characterization confirmed their possible involvement in shaping up the homeostasis of cells in the mature biofilm.Interestingly, in our study, upregulation of the genes (such as CgICL1, CgMLS1, CgPCK1 andCgNTH1) within biofilm cells of clinical isolate of C. glabratais associated with carbon metabolism.This suggested that C. glabrata encounters a dearth Firstly, it may adopt an alternative glyoxylate pathways instead of tricarboxylic acid cycle (TCA), where glyoxylate is biosynthesized from isocitrate, catalysed by a key enzyme isocitrate lyase (ICL1) and subsequently glyoxylate is converted into malate using malate synthase enzyme (MLS1) (Fig. 9) [50,52].These observations suggest that C. glabrata bypass the two-carboxylation steps of the TCA cycle (Isocitrate to alpha-ketoglutarate and subsequently to Succinyl CoA) in mature biofilm conditions that enhance its virulence [52,55,56].It is in accordance with earlier studies, where it has been demonstrated that the metabolic plasticity of C. glabrata modulates the virulence and survival ability in nutrient-starved condition to counter the stress in a biofilm growth phase and channelizes to promote pathogenicity from commensal to opportunistic mode [57][58][59].Secondly, it may follow gluconeogenesis pathway by mediating the upregulated expression of CgPCK1, which has been reported previously in the reprogramming and regulation of carbon assimilation in pathogenic C. albicans [60].Thirdly, C. glabrata(NCCPF-100,037) cells may also hydrolyse the trehalose into two glucose units to overcome the glucose scarcity in mature biofilm with enhanced trehalase (NTH1) enzyme expression, which has been reported previously in S. cerevisiae [61,62].These pathways are interconnected and enhance fitness attributes and metabolic rewiring in the biofilm lifestyle of C. glabrata.
After comprehensive analysis of DEGs next we chose two genes (CgPCK1 and CgPEP1), whose expression was significantly elevated under mature biofilm of C. glabrata (NCCPF − 100,037).Previous reports have shown that under biofilm growth mode, C. glabrata encounters nutrient and oxidative stress conditions [52].Thus, to confirm their role in resistance towards stresses prevailing in the mature growth mode of C. glabrata (NCCPF − 100,037), we knocked-out the respective genes using a cassette deletion approach.Firstly, we investigated whether CgPCK1 expression is associated with nutrient stress of the preferred carbon source and how it overcomes this.Phenotype profiling results of our study with Cgpck1∆ and wild strain of C. glabrata (NCCPF − 100,037) on alternative carbon sources (glycerol, ethanol, and oleic acid) confirmed that the CgPCK1 gene is essential to assimilate and metabolize the glycerol, ethanol, and oleic acid.These results suggest that in the absence of glucose, C. glabrata assimilate glycerol, oleic acid and generate acetyl coenzyme A (acetyl-CoA) which is a central and connecting metabolite between catabolic to anabolic pathways (glyoxylate and gluconeogenesis) to produce glucose and fulfil energy requirements.The key gene (CgPCK1) which encode the enzyme to Phosphoenolpyruvate (PEP) carboxykinase to produce acetyl coenzyme A (acetyl-CoA) through PEP from oxaloacetate of glyoxylate cycle plays an important role in this carbon assimilation pathways.These findings are in concordance with previous reports where they have reported alternative carbon metabolism in the virulence of C. albicans and fitness attribute of S. cerevisiae [50,63,64].Thus, our transcriptomic and functional genomic observations showed its overexpression and functional validation in the biofilm of C. glabrata.These findings, were also in line with previous observations where overexpression of CgPCK1 were documented in the reprogramming and regulation of carbon assimilation in pathogenic C. albicans [60].NMR spectroscopy based metabolic profiling in C. glabrata underscores the significant reorganization of carbon metabolic pathways according to the suitable carbon substrate, indicating that this pathogen successfully adapts to varied physiological conditions [65].
In second gene deletion experiment, we knockedout CgPEP1 to examine whether CgPEP1 expression is involved in oxidative stress resistance.Here, we assessed the growth phenotype of wild and Cgpep1∆ strains of C. glabrata (NCCPF − 100,037) with H 2 O 2 and observed phenotype profiling.Growth impairment of Cgpep1∆ strains of C. glabrata in the presence H 2 O 2 suggested that CgPEP1 is involved in countering the ROS stress of H 2 O 2 .Gene deletion of CgPEP1 along with phenotype profiling of mutant strain, indicated its role in the degradation and sorting of oxidatively damaged proteins and counter the oxidative stress damage due to hydrogen peroxide in mature the biofilm of C. glabrata (NCCPF-100,037) and prevent cell death.This is in accordance with previous study where PEP4 was reported to be associated with oxidative stress in S. cerevisiae [66][67][68].The current study highlighted that (i) Up-regulation of CgICL, CgMLS and-CgPCK1 genes are involved in the glyoxylate cycle and gluconeogenesis pathway are up-regulated in the biofilm growth phase (ii) Deletion of (CgPCK1 and CgPEP1) genes, confirmed their role in nutrient and oxidative stress under mature biofilm growth phase of C. glabrata (NCCPF100037).Thus, the information obtained from the present study can be concluded that genes CgICL, CgMLS and CgPCK1 are involved in the glyoxylate cycle and could be used as novel antifungal targets to treat candidiasis caused by C. glabrata.

Conclusion
The current study deciphered the important genes, gene sets and their interactome that could play a pivotal in the biofilm formation.Additionally, the gene deletion approach confirmed the role of CgPCK1 in alternative carbon source assimilation and CgPEP1 in protein sorting to counter the nutrient and oxidative stress prevailing in the mature biofilm of C. glabrata (NCPPF-100,037).Thus, the study demonstrated that up-regulation of CgICL, CgMLS and CgPCK1 are associated with the glyoxylate cycle and gluconeogenesis pathways.The observations deduced from the present study along with future work on characterization of the proteins involved in this intricate process may prove to be beneficial for designing novel antifungal strategies.

Fig. 1
Fig. 1 Comparative evaluation of the biofilm forming potential of five different strains of C. glabrata assessed by the crystal violet and XTT assay: (a)Comparative biomass formation by five strains of C. glabrata evaluated using crystal violet assay, all strains showed an increasing trend of biomass up to 120 h.X-axis represents the time of incubation up to 120 h of all strains under investigation, and Y-axis represents the optical density (OD) values taken at 690 nm (b) Metabolic activity of cells in the biofilm growth phase of all the tested C. glabrata strains evaluated using XTT assay and monitored for 120 h at different time points showed a decreasing trend of OD in all the strains.The ODs presented are the mean +/-standard deviation of three individual ODs evaluated in triplicate with p value < 0.05.Bar graph were drawn using GraphPad Prism (v 5.01) Biofilm morphology and architecture of all five strains was visualized with both confocal laser scanning microscopy (CLSM).It was interesting to observe that comparative analysis of 1-dimensional (1-D) CLSM photomicrographs of all strains exhibited a similar pattern of fluorescent red cylindrical intravacuolar structures (CIVS) with equal fluorescence stained with FUN-1[2chloro4(2,3 dihydro-3-methyl (benzo-1,3-thiazol 2-yl)-methylidene)1 phenyl quinolinium iodide].Dense CIVS in red color reflects the viability of cells, this indicates that metabolically active cells are present in the biofilm phase of all strains (Fig. 2I, a-e).Comparative investigation of 3-D reconstructed projection of

Fig. 2
Fig. 2 CLSM photomicrographs of biofilm growth phase of five strains of C. glabrata: (a) ATCC-2001; (b) MTCC-3019; (c) NCCPF-100,037; (d) NCCPF-100,033; (e) NCCPF-100,029.Panel I (a, b, c, d and e) represents 1-D CLSM images of C. glabrata strains ATCC-2001, MTCC-3019, NCCPF-100,037, NCCPF-100,033 & NCCPF-100,029, respectively.Panel II (a, b, c, d, and e) represents the images clicked through different contrast and sections to show the overall morphology and architecture of biofilm of all strains in a similar order.Panel III (a, b, c, d, and e) represents one stack out of many stacks captured and a side view reconstructed by Leica application suite (LAS − X) software to visualize the 3-D projection of biofilm thickness of all strains observed

Fig. 3
Fig. 3 Volcano plot of the DEGs in planktonic and biofilm growth phase of C. glabrata.DEGs under individual experimental conditions (planktonic and biofilm) of C. glabrata.The X-axis represents the normalised expression of genes in terms of log2 fold change (log 2 FC), and dots in green and red color demonstrate the significant downregulated and upregulated genes respectively.Y-axis represents statistical significance (p-value)

Fig. 4 14 Fig. 6 Fig. 5
Fig.4 Hierarchical clustering significant DEGs in biofilm growth mode: Shows the top significant up-regulated genes, columns represent the planktonic and biofilm growth condition of C. glabrata(Fig.4a)similarly the up-regulated genes are shown in (Fig.4b) .Expression of the significant DEGs (listed on the right side of the columns along their encoded proteins) plotted according to their normalized log2FC (FPKM) values in z-scores.Gene expression values of different DEGs are presented in color key code of heatmap with a scale bar of with a heat map of a color scale bar 0-14

Functional classification, gene ontology and pathway analysis of DEGs
42, 76.24, 76.42, 74.38, 68.06 & 86.6% ,respectively, listed in, (Supplementary Table (Supplementary TableS3).The entire highthroughput transcriptomic sequence data of six samples was investigated to identify differentially expressed genes (DEG) in the mature biofilm growth phase of C. glabrata (NCCPF-100,037).The expression features detail of differentially expressed genes (DEGs) under both growth conditions such as gene ID, gene locus, normalised expression count in terms of FPKM values, p-value, adjusted p-value (FDR), transcript ID, transcription start site IDs, class codes, gene annotation, encoded protein, gene ontology annotation of significantly expressed top 50 up-regulated and down-regulated genes is presented in the, (Supplementary Table(Supplementary Table